Bump torchvision from 0.16.0+cu121 to 0.17.1

[dependabot]

Bumps torchvision from 0.16.0+cu121 to 0.17.1.

Release notes

Sourced from torchvision's releases.

TorchVision 0.17.1 Release

This is a patch release, which is compatible with PyTorch 2.2.1.

Bug Fixes

• Add gdown dependency to support downloading datasets from Google Drive (pytorch/vision#8237)
• Fix silent correctness with convert_bounding_box_format when passing string parameters (pytorch/vision#8258)

TorchVision 0.17 Release

Highlights

The V2 transforms are now stable!

The torchvision.transforms.v2 namespace was still in BETA stage until now. It is now stable! Whether you’re new to Torchvision transforms, or you’re already experienced with them, we encourage you to start with Getting started with transforms v2 in order to learn more about what can be done with the new v2 transforms.

Browse our main docs for general information and performance tips. The available transforms and functionals are listed in the API reference. Additional information and tutorials can also be found in our example gallery, e.g. Transforms v2: End-to-end object detection/segmentation example or How to write your own v2 transforms.

Towards torch.compile() support

We are progressively adding support for torch.compile() to torchvision interfaces, reducing graph breaks and allowing dynamic shape.

The torchvision ops (nms, [ps_]roi_align, [ps_]roi_pool and deform_conv_2d) are now compatible with torch.compile and dynamic shapes.

On the transforms side, the majority of low-level kernels (like resize_image() or crop_image()) should compile properly without graph breaks and with dynamic shapes. We are still addressing the remaining edge-cases, moving up towards full functional support and classes, and you should expect more progress on that front with the next release.

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Detailed Changes

Breaking changes / Finalizing deprecations

• [transforms] We changed the default of the antialias parameter from None to True, in all transforms that perform resizing. This change of default has been communicated in previous versions, and should drastically reduce the amount of bugs/surprises as it aligns the tensor backend with the PIL backend. Simply put: from now on, antialias is always applied when resizing (with bilinear or bicubic modes), whether you're using tensors or PIL images. This change only affects the tensor backend, as PIL always applies antialias anyway. (#7949)
• [transforms] We removed the torchvision.transforms.functional_tensor.py and torchvision.transforms.functional_pil.py modules, as these had been deprecated for a while. Use the public functionals from torchvision.transforms.v2.functional instead. (#7953)
• [video] Remove deprecated path parameter to VideoReader and made src mandatory (#8125)
• [transforms] to_pil_image now provides the same output for equivalent numpy arrays and tensor inputs (#8097)

Bug Fixes

[datasets] Fix root path expansion in datasets.Kitti (#8165) [transforms] allow sequence fill for v2 AA scripted (#7919) [reference scripts] Fix quantized references (#8073) [reference scripts] Fix IoUs reported in segmentation references (#7916)

New Features

[datasets] add Imagenette dataset (#8139)

... (truncated)

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[dependabot]

Superseded by #16.